7 Search Results for "Azarmehr, Amir"

Document
DOI: 10.4230/LIPIcs.ITCS.2026.51
Near-Optimal Sparsifiers for Stochastic Knapsack and Assignment Problems

Authors: Shaddin Dughmi, Yusuf Hakan Kalayci, and Xinyu Liu

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract
When uncertainty meets costly information gathering, a fundamental question emerges: which data points should we probe to unlock near-optimal solutions? Sparsification of stochastic packing problems addresses this trade-off. The existing notions of sparsification measure the level of sparsity, called degree, as the ratio of queried items to the optimal solution size. While effective for matching and matroid-type problems with uniform structures, this cardinality-based approach fails for knapsack-type constraints where feasible sets exhibit dramatic structural variation. We introduce a polyhedral sparsification framework that measures the degree as the smallest scalar needed to embed the query set within a scaled feasibility polytope, naturally capturing redundancy without relying on cardinality. Our main contribution establishes that knapsack, multiple knapsack, and generalized assignment problems admit (1-ε)-approximate sparsifiers with degree polynomial in 1/p and 1/ε - where p denotes the independent activation probability of each element - remarkably independent of problem dimensions. The key insight involves grouping items with similar weights and deploying a charging argument: when our query set misses an optimal item, we either substitute it directly with a queried item from the same group or leverage that group’s excess contribution to compensate for the loss. This reveals an intriguing complexity-theoretic separation - while the multiple knapsack problem lacks an FPTAS and generalized assignment is APX-hard, their sparsification counterparts admit efficient (1-ε)-approximation algorithms that identify polynomial degree query sets. Finally, we raise an open question: can such sparsification extend to general integer linear programs with degree independent of problem dimensions?
Cite as

Shaddin Dughmi, Yusuf Hakan Kalayci, and Xinyu Liu. Near-Optimal Sparsifiers for Stochastic Knapsack and Assignment Problems. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 51:1-51:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{dughmi_et_al:LIPIcs.ITCS.2026.51,
  author =	{Dughmi, Shaddin and Kalayci, Yusuf Hakan and Liu, Xinyu},
  title =	{{Near-Optimal Sparsifiers for Stochastic Knapsack and Assignment Problems}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{51:1--51:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.51},
  URN =		{urn:nbn:de:0030-drops-253386},
  doi =		{10.4230/LIPIcs.ITCS.2026.51},
  annote =	{Keywords: Packing Problems, Assignment Problems, Stochastic Selection, Sparsification}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.64
Fully Scalable MPC Algorithms for Euclidean k-Center

Authors: Artur Czumaj, Guichen Gao, Mohsen Ghaffari, and Shaofeng H.-C. Jiang

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)

Abstract
The k-center problem is a fundamental optimization problem with numerous applications in machine learning, data analysis, data mining, and communication networks. The k-center problem has been extensively studied in the classical sequential setting for several decades, and more recently there have been some efforts in understanding the problem in parallel computing, on the Massively Parallel Computation (MPC) model. For now, we have a good understanding of k-center in the case where each local MPC machine has sufficient local memory to store some representatives from each cluster, that is, when one has Ω(k) local memory per machine. While this setting covers the case of small values of k, for a large number of clusters these algorithms require undesirably large local memory, making them poorly scalable. The case of large k has been considered only recently for the fully scalable low-local-memory MPC model for the Euclidean instances of the k-center problem. However, the earlier works have been considering only the constant dimensional Euclidean space, required a super-constant number of rounds, and produced only k(1+o(1)) centers whose cost is a super-constant approximation of k-center. In this work, we significantly improve upon the earlier results for the k-center problem for the fully scalable low-local-memory MPC model. In the low dimensional Euclidean case in ℝ^d, we present the first constant-round fully scalable MPC algorithm for (2+ε)-approximation. We push the ratio further to (1 + ε)-approximation albeit using slightly more (1 + ε)k centers. All these results naturally extends to slightly super-constant values of d. In the high-dimensional regime, we provide the first fully scalable MPC algorithm that in a constant number of rounds achieves an O(log n/ log log n)-approximation for k-center.
Cite as

Artur Czumaj, Guichen Gao, Mohsen Ghaffari, and Shaofeng H.-C. Jiang. Fully Scalable MPC Algorithms for Euclidean k-Center. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 64:1-64:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{czumaj_et_al:LIPIcs.ICALP.2025.64,
  author =	{Czumaj, Artur and Gao, Guichen and Ghaffari, Mohsen and Jiang, Shaofeng H.-C.},
  title =	{{Fully Scalable MPC Algorithms for Euclidean k-Center}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{64:1--64:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.64},
  URN =		{urn:nbn:de:0030-drops-234416},
  doi =		{10.4230/LIPIcs.ICALP.2025.64},
  annote =	{Keywords: Massively Parallel Computing, Euclidean Spaces, k-Center Clustering}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.116
A 0.51-Approximation of Maximum Matching in Sublinear n^{1.5} Time

Authors: Sepideh Mahabadi, Mohammad Roghani, and Jakub Tarnawski

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)

Abstract
We study the problem of estimating the size of a maximum matching in sublinear time. The problem has been studied extensively in the literature and various algorithms and lower bounds are known for it. Our result is a 0.5109-approximation algorithm with a running time of Õ(n√n). All previous algorithms either provide only a marginal improvement (e.g., 2^{-280}) over the 0.5-approximation that arises from estimating a maximal matching, or have a running time that is nearly n². Our approach is also arguably much simpler than other algorithms beating 0.5-approximation.
Cite as

Sepideh Mahabadi, Mohammad Roghani, and Jakub Tarnawski. A 0.51-Approximation of Maximum Matching in Sublinear n^{1.5} Time. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 116:1-116:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{mahabadi_et_al:LIPIcs.ICALP.2025.116,
  author =	{Mahabadi, Sepideh and Roghani, Mohammad and Tarnawski, Jakub},
  title =	{{A 0.51-Approximation of Maximum Matching in Sublinear n^\{1.5\} Time}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{116:1--116:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.116},
  URN =		{urn:nbn:de:0030-drops-234932},
  doi =		{10.4230/LIPIcs.ICALP.2025.116},
  annote =	{Keywords: Sublinear Algorithms, Maximum Matching, Maximal Matching, Approximation Algorithm}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.66
One-Way Communication Complexity of Minimum Vertex Cover in General Graphs

Authors: Mahsa Derakhshan, Andisheh Ghasemi, and Rajmohan Rajaraman

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)

Abstract
We study the communication complexity of the Minimum Vertex Cover (MVC) problem on general graphs within the k-party one-way communication model. Edges of an arbitrary n-vertex graph are distributed among k parties. The objective is for the parties to collectively find a small vertex cover of the graph while adhering to a communication protocol where each party sequentially sends a message to the next until the last party outputs a valid vertex cover of the whole graph. We are particularly interested in the trade-off between the size of the messages sent and the approximation ratio of the output solution. It is straightforward to see that any constant approximation protocol for MVC requires communicating Ω(n) bits. Additionally, there exists a trivial 2-approximation protocol where the parties collectively find a maximal matching of the graph greedily and return the subset of vertices matched. This raises a natural question: What is the best approximation ratio achievable using optimal communication of O(n)? We design a protocol with an approximation ratio of (2-2^{-k+1}+ε) and O(n) communication for any desirably small constant ε > 0, which is strictly better than 2 for any constant number of parties. Moreover, we show that achieving an approximation ratio smaller than 3/2 for the two-party case requires n^{1 + Ω(1/lg lg n)} communication, thereby establishing the tightness of our protocol for two parties. A notable aspect of our protocol is that no edges are communicated between the parties. Instead, for any 1 ≤ i < k, the i-th party only communicates a constant number of vertex covers for all edges assigned to the first i parties. An interesting consequence is that the communication cost of our protocol is O(n) bits, as opposed to the typical Ω(nlog n) bits required for many graph problems, such as maximum matching, where protocols commonly involve communicating edges.
Cite as

Mahsa Derakhshan, Andisheh Ghasemi, and Rajmohan Rajaraman. One-Way Communication Complexity of Minimum Vertex Cover in General Graphs. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 66:1-66:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{derakhshan_et_al:LIPIcs.ICALP.2025.66,
  author =	{Derakhshan, Mahsa and Ghasemi, Andisheh and Rajaraman, Rajmohan},
  title =	{{One-Way Communication Complexity of Minimum Vertex Cover in General Graphs}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{66:1--66:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.66},
  URN =		{urn:nbn:de:0030-drops-234430},
  doi =		{10.4230/LIPIcs.ICALP.2025.66},
  annote =	{Keywords: Communication Complexity, Minimum Vertex Cover}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2025.67
Query Efficient Weighted Stochastic Matching

Authors: Mahsa Derakhshan and Mohammad Saneian

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)

Abstract
In this paper, we study the weighted stochastic matching problem. Let G = (V, E) be a given edge-weighted graph, and let its realization 𝒢 be a random subgraph of G that includes each edge e ∈ E independently with a known probability p_e. The goal in this problem is to pick a sparse subgraph Q of G without prior knowledge of 𝒢, such that the maximum weight matching among the realized edges of Q (i.e., the subgraph Q ∩ 𝒢) in expectation approximates the maximum weight matching of the entire realization 𝒢. It is established by previous work that attaining any constant approximation ratio for this problem requires selecting a subgraph of max-degree Ω(1/p), where p = min_{e ∈ E} p_e. On the positive side, there exists a (1-ε)-approximation algorithm by Behnezhad and Derakhshan [FOCS'20], albeit at the cost of a max-degree having exponential dependence on 1/p. Within the O(1/p) query regime, however, the best-known algorithm achieves a 0.536 approximation ratio due to Dughmi, Kalayci, and Patel [ICALP'23], improving over the 0.501 approximation algorithm by Behnezhad, Farhadi, Hajiaghayi, and Reyhani [SODA'19]. In this work, we present a 0.68-approximation algorithm with the asymptotically optimal O(1/p) queries per vertex. Our result not only substantially improves the approximation ratio for weighted graphs, but also breaks the well-known 2/3 barrier with the optimal number of queries - even for unweighted graphs. Our analysis involves reducing the problem to designing a randomized matching algorithm on a given stochastic graph with some variance-bounding properties. To achieve these properties, we leverage a randomized algorithm by MacRury and Ma [STOC'24] for a variant of online stochastic matching.
Cite as

Mahsa Derakhshan and Mohammad Saneian. Query Efficient Weighted Stochastic Matching. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 67:1-67:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{derakhshan_et_al:LIPIcs.ICALP.2025.67,
  author =	{Derakhshan, Mahsa and Saneian, Mohammad},
  title =	{{Query Efficient Weighted Stochastic Matching}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{67:1--67:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.67},
  URN =		{urn:nbn:de:0030-drops-234445},
  doi =		{10.4230/LIPIcs.ICALP.2025.67},
  annote =	{Keywords: Sublinear algorithms, Stochastic, Matching}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2025.74
Sublinear Metric Steiner Tree via Improved Bounds for Set Cover

Authors: Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski, and Ali Vakilian

Published in: LIPIcs, Volume 325, 16th Innovations in Theoretical Computer Science Conference (ITCS 2025)

Abstract
We study the metric Steiner tree problem in the sublinear query model. In this problem, for a set of n points V in a metric space given to us by means of query access to an n× n matrix w, and a set of terminals T ⊆ V, the goal is to find the minimum-weight subset of the edges that connects all the terminal vertices. Recently, Chen, Khanna and Tan [SODA'23] gave an algorithm that uses Õ(n^{13/7}) queries and outputs a (2-η)-estimate of the metric Steiner tree weight, where η > 0 is a universal constant. A key component in their algorithm is a sublinear algorithm for a particular set cover problem where, given a set system (𝒰, ℱ), the goal is to provide a multiplicative-additive estimate for |𝒰|-SC(𝒰, ℱ). Here 𝒰 is the set of elements, ℱ is the collection of sets, and SC(𝒰, ℱ) denotes the optimal set cover size of (𝒰, ℱ). In particular, their algorithm returns a (1/4, ε⋅|𝒰|)-multiplicative-additive estimate for this set cover problem using Õ(|ℱ|^{7/4}) membership oracle queries (querying whether a set S ∈ 𝒮 contains an element e ∈ 𝒰), where ε is a fixed constant. In this work, we improve the query complexity of (2-η)-estimating the metric Steiner tree weight to Õ(n^{5/3}) by showing a (1/2, ε⋅|𝒰|)-estimate for the above set cover problem using Õ(|ℱ|^{5/3}) membership queries. To design our set cover algorithm, we estimate the size of a random greedy maximal matching for an auxiliary multigraph that the algorithm constructs implicitly, without access to its adjacency list or matrix. Previous analyses of random greedy maximal matching have focused on simple graphs, assuming access to their adjacency list or matrix. To address this, we extend the analysis of Behnezhad [FOCS'21] of random greedy maximal matching on simple graphs to multigraphs, and prove additional properties that may be of independent interest.
Cite as

Sepideh Mahabadi, Mohammad Roghani, Jakub Tarnawski, and Ali Vakilian. Sublinear Metric Steiner Tree via Improved Bounds for Set Cover. In 16th Innovations in Theoretical Computer Science Conference (ITCS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 325, pp. 74:1-74:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{mahabadi_et_al:LIPIcs.ITCS.2025.74,
  author =	{Mahabadi, Sepideh and Roghani, Mohammad and Tarnawski, Jakub and Vakilian, Ali},
  title =	{{Sublinear Metric Steiner Tree via Improved Bounds for Set Cover}},
  booktitle =	{16th Innovations in Theoretical Computer Science Conference (ITCS 2025)},
  pages =	{74:1--74:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-361-4},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{325},
  editor =	{Meka, Raghu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2025.74},
  URN =		{urn:nbn:de:0030-drops-227029},
  doi =		{10.4230/LIPIcs.ITCS.2025.74},
  annote =	{Keywords: Sublinear Algorithms, Steiner Tree, Set Cover, Maximum Matching, Approximation Algorithm}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2023.14
Robust Communication Complexity of Matching: EDCS Achieves 5/6 Approximation

Authors: Amir Azarmehr and Soheil Behnezhad

Published in: LIPIcs, Volume 261, 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)

Abstract
We study the robust communication complexity of maximum matching. Edges of an arbitrary n-vertex graph G are randomly partitioned between Alice and Bob independently and uniformly. Alice has to send a single message to Bob such that Bob can find an (approximate) maximum matching of the whole graph G. We specifically study the best approximation ratio achievable via protocols where Alice communicates only Õ(n) bits to Bob. There has been a growing interest on the robust communication model due to its connections to the random-order streaming model. An algorithm of Assadi and Behnezhad [ICALP'21] implies a (2/3+ε₀ ∼ .667)-approximation for a small constant 0 < ε₀ < 10^{-18}, which remains the best-known approximation for general graphs. For bipartite graphs, Assadi and Behnezhad [Random'21] improved the approximation to .716 albeit with a computationally inefficient (i.e., exponential time) protocol. In this paper, we study a natural and efficient protocol implied by a random-order streaming algorithm of Bernstein [ICALP'20] which is based on edge-degree constrained subgraphs (EDCS) [Bernstein and Stein; ICALP'15]. The result of Bernstein immediately implies that this protocol achieves an (almost) (2/3 ∼ .666)-approximation in the robust communication model. We present a new analysis, proving that it achieves a much better (almost) (5/6 ∼ .833)-approximation. This significantly improves previous approximations both for general and bipartite graphs. We also prove that our analysis of Bernstein’s protocol is tight.
Cite as

Amir Azarmehr and Soheil Behnezhad. Robust Communication Complexity of Matching: EDCS Achieves 5/6 Approximation. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 14:1-14:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{azarmehr_et_al:LIPIcs.ICALP.2023.14,
  author =	{Azarmehr, Amir and Behnezhad, Soheil},
  title =	{{Robust Communication Complexity of Matching: EDCS Achieves 5/6 Approximation}},
  booktitle =	{50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)},
  pages =	{14:1--14:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-278-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{261},
  editor =	{Etessami, Kousha and Feige, Uriel and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2023.14},
  URN =		{urn:nbn:de:0030-drops-180666},
  doi =		{10.4230/LIPIcs.ICALP.2023.14},
  annote =	{Keywords: Maximum Matching, Robust Communication Complexity, Edge Degree Constrained Subgraph}
}
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